Special Issue "Entropy and Information"

Guest Editor
Dr. Peter Harremoës ^*
Centrum Wiskunde & Informatica (CWI), Science Park 123, 1098 XG Amsterdam, The Netherlands
Website: http://homepages.cwi.nl/~ph/
E-Mail:
Interests: symmetry, information divergence, cause and effect, Maxwell's demon, probability and statistics
^* Dr. Harremoës also serves as the Editor-in-Chief of Entropy

Submission

All papers should be submitted to entropy@mdpi.org with copy to the guest editor. To be published continuously until the deadline and papers will be listed together at the special websites. Both, research articles and review articles are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editors for announcment on this website.

Submitted papers should not have been published previously, nor be under consideration for publication elsewhere. All papers are refereed through a peer-review process. A guide for authors, sample copies and other relevant information for submitting papers are available on the Instructions for Authors page. Entropy is an international peer-reviewed quarterly journal published by Molecular Diversity Preservation International.

Please visit the Instructions for Authors page before submitting a paper. Open Access publication fees are 800 CHF per paper. English correction fees (250 CHF) will be added in certain cases (1050 CHF per paper for those papers that require extensive additional formatting and/or English corrections.).

• entropy
• information
• information theory

Title: Paradigms of Cognition
Author: Flemming Topsøe
Affiliation: University of Copenhagen, Department of Mathematical Sciences, Universitetsparken 5, 2100 Copenhagen, Denmark
Abstract: Cognition strives for knowledge} of truth. Our analysis builds on interaction which leads from truth and belief to knowledge. Different interactions are considered, each defining a particular world. Examples include the classical world, where truth is observable, black holes and mixtures of these. The observer will attempt to adapt observation strategies to the world. This involves description. Entropy is defined as minimal description effort. This in itself as well as a possible connection to coding} provides a transparent interpretation of entropy and other quantities of information. In particular, this applies to the notions of entropy now known as Tsallis entropy.

Type of Paper: Article
Title: A Lower-Bound for the Maximin Redundancy in Pattern Coding
Author: Aurelien Garivier
Affiliation: CNRS, Telecom ParisTech, Laboratoire Laboratoire Traitement et Communication de l’Information, 75013 Paris, France; E-Mail: aurelien.garivier@telecom-paristech.fr
Abstract: We show that the maximin average redundancy in pattern coding is eventually larger than 1.84 (n / logn)^1/3 for messages of length n. This completes the results obtained recently on pattern redundancy, although it does not fill the gap between known lower- and upper-bounds. The problem of pattern coding raised much interest recently, as strongly universal codes have been proved to exist for patterns while universal message coding is impossible for memoryless sources on an infinite alphabet. The proof uses fine combinatorial results on partitions with small summands.

Type of Paper: Article
Title: Role of Entropy-Based Class Uncertainty in Image Segmentation: A Study with Different Approaches
Authors: Yinxiao Liu , Guoyuan Liang , Punam K Saha
Affiliation: Department of Electrical and Computer Engineering and Department of Radiology, University of Iowa, Iowa City, IA 52242, USA
Abstract: Image segmentation is of paramount interest in many applications, especially, those involving perception of symbolic, syntactic, or high level cognitive knowledge. Role of entropy, an expression of image information, has primarily been investigated in image thresolding. However, research efforts on combining entropy into general segmentation frameworks were previously missing. Recently, we have developed a new theory of entropy-based class uncertainty revealing its synergy with image-derived features that has opened a new research avenue of fitting entropy into general image segmentation frameworks. In this paper, we study applications of class uncertainty in thresholding and gradient optimization, and in other segmentation approaches including fuzzy connectedness, deformable contours, and active shape models.
Keywords: Entropy, class uncertainty, segmentation, probability, energy surface, optimization.

Type of Paper: Review
Title: Quantum Entropy and Its Applications to Quantum Communication and Statistical Physics
Authors: Masanori Ohya and Noboru Watanabe
Affiliation: Department of Information Sciences, Tokyo University of Science, 2641 Yamazaki, NodaCity, Chiba 278-8510, Japan; E-Mails: ohya@rs.noda.tus.ac.jp; watanabe@is.noda.tus.ac.jp
Abstract: Quantum entropy is a fundamental concept for quantum information recently developed in various directions. We will review the fundamental aspects of quantum entropy (entropies) and discuss some applications to quantum communication, statistical physics, etc.